Data Engineer Lead

Start free →

Or apply yourself on the official page →

About the role

Job Description Build and maintain scalable data solutions to support marketing analytics and audience activation initiatives , with a strong focus on Databricks, governed data structures, reusable components, and reliable data pipelines. The ideal candidate has strong experience working with Databricks, Git-based development workflows, marketing performance data, customer identity matching, and data governance . You will work with data from multiple enterprise sources, transform legacy audience logic into governed definitions, and build reliable data products that support analytics and downstream activation. Responsibilities • Develop and maintain scalable data pipelines in Databricks , using Unity Catalog and Delta . • Curate Genie spaces and semantic layers , including table and column metadata, certified metric definitions, example SQL, and trusted assets. • Maintain and refactor existing Git/GitHub repositories , developing modular and reusable data components. • Implement CI/CD workflows for Databricks solutions, including promotion from development to controlled UAT environments. • Model marketing performance data including email events, campaign and promotion history, offers, packages, and tours . • Build point-in-time audience histories and connect marketing sends with downstream sales outcomes. • Develop data solutions at the person and household grain , using ID crosswalks and match rules based on existing identity resolution outputs. • Implement suppression and consent requirements , including Do Not Email rules, marketability flags, and PII handling. • Ingest and integrate data from SQL Server enterprise data warehouses and translate legacy SQL audience logic into governed definitions. • Deliver audiences from Databricks to Adobe Campaign or Segment , including service accounts, encryption, and auditing. • Profile unfamiliar data sources independently, producing data dictionaries and ERDs and verifying data availability and structure. • Develop data quality tests and validated query/result sets to support reliable datasets and agent evaluation. • Collaborate with analytics, engineering, marketing, data, and security teams to improve data solutions and processes.   Qualifications • 5+ years of experience in Data Engineering or similar roles. • Hands-on experience developing data pipelines in Databricks , including Unity Catalog and Delta . • Strong hands-on experience with Python for data processing and transformation. • Strong SQL skills, including the ability to understand and translate complex existing SQL logic. • Experience with Git-based development and CI/CD , preferably using Databricks Asset Bundles or an equivalent approach. • Experience with Azure and promoting data solutions across development and controlled UAT environments. • Experience modeling data for marketing analytics, customer data, or similar business domains . • Experience with customer identity, person/household data, ID crosswalks, and identity matching rules . • Experience handling consent, suppression, marketability, and PII requirements . • Experience integrating data from SQL Server enterprise data warehouses . • Ability to independently profile unfamiliar data sources and document findings through data dictionaries and ERDs. • Strong analytical and problem-solving skills, with the ability to investigate ambiguous data issues independently. • Strong communication and collaboration skills for working with technical and business stakeholders. What about languages? • You will need excellent written and verbal English for clear and effective communication with the team. How much experience must I have? • In order to thrive in this role, you must have at least 5+ years of experience in data engineering or similar

View the official posting →